simonorozcoarias / ML_DL_microArrays
Here, we describe the comparison of the most used algorithms in classical ML and DL to classify carcinogenic tumors described on 11_tumor data base, obtaining accuracies between 76.97% and 100% for tumor identification. Our results bring up a more efficient an accurate classification method based on gene expression (microarray data) and ML/DL al…
☆10Updated 5 years ago
Alternatives and similar repositories for ML_DL_microArrays:
Users that are interested in ML_DL_microArrays are comparing it to the libraries listed below
- OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data☆11Updated 2 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- This repository contains code used to build and interpret a deep learning model. It is a DNN classifier trained using gene expression dat…☆9Updated 3 years ago
- ☆14Updated last year
- This is the repository for paper titled as "Convolutional neural network models for cancer type prediction based on gene expression".☆51Updated 5 years ago
- Clinical data for the TCGA PanCancer Atlas☆14Updated 5 years ago
- ☆34Updated 2 years ago
- Deep-Learning framework for multi-omic and survival data integration☆82Updated last year
- ☆54Updated 2 years ago
- ☆17Updated 5 years ago
- ☆34Updated 3 years ago
- SALMON: Survival Analysis Learning with Multi-Omics Neural Networks☆67Updated 5 months ago
- Reproducing the experiments of the DestVI paper☆18Updated 3 years ago
- Containerized cancer subtype prediction tools for gene expression, miRNA, DNA methylation, somatic mutations and copy number variation.☆23Updated 2 weeks ago
- Spatial cellular architecture predicts prognosis in glioblastoma - Nature Communications☆24Updated last year
- MOMA: A Multi-task Attention Learning Algorithm for Multi-omics Data Interpretation and Classification☆16Updated 2 years ago
- using shallow neural network layer (embedding) to infer gene-gene/sample relationship from gene expression data☆21Updated 6 years ago
- SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention☆38Updated last month
- Pathway-based sparse deep neural network for survival analysis☆38Updated last year
- A Snapshot Neural Ensemble Method for Cancer Type Prediction Based on Copy Number Variations☆20Updated 2 years ago
- Using traditional machine learning and deep learning methods to predict stuff from TCGA pathology slides.☆18Updated 6 years ago
- jupyter notebook; perform differential gene expression analysis using DESeq2 on TCGA RNAseq data☆32Updated 6 years ago
- ALD study data analysis☆13Updated 2 years ago
- repository with the scripts to run examples of the publications with new functionalities of TCGAbiolinks☆15Updated 3 years ago
- Morphology-Enhanced Spatial Transcriptome Analysis Integrator☆25Updated last month
- ☆18Updated last year
- ☆26Updated 4 years ago
- Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-m…☆20Updated 4 months ago
- ☆14Updated 2 years ago
- Multi-task deep learning framework for multi-omics data analysis☆45Updated 2 years ago